A review of unmanned vehicle distribution optimization models and algorithms

IF 7.4 2区 工程技术 Q1 ENGINEERING, CIVIL
Jiao Zhao , Hui Hu , Yi Han , Yao Cai
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Abstract

With the development of globalization and artificial intelligence, as well as the outbreak of COVID-19, unmanned vehicles have played an important role in cargo distribution. In order to better analyze the research directions of unmanned vehicle distribution, this paper summarizes the models and algorithms of unmanned vehicle distribution optimization. The research results show that most of the studies have established the goal of optimizing the total costs or travel time. Many researchers have begun to study multi-objective optimization problems, but there are certain limitations, so some studies convert these problems into single-objective optimization for solving, such as converting time and energy consumption into cost, waiting time into distance, and time delay into penalty cost. With the development of unmanned vehicle distribution technology, in future research, a multi-objective model with the lowest cost, the shortest distance and the best security should be established and solved. Most studies have proposed heuristic algorithms for solving the unmanned vehicle distribution problem, and improved optimization solutions have been obtained. In order to ensure the diversity of solution methods, and give consideration to solution time and solution quality, hybrid methods with other algorithms will be a future research direction, for example, the combination of heuristic algorithm and exact algorithm. With the gradual deepening of research, integrated distribution of multiple types of unmanned equipment will become the focus of future research.

无人车配送优化模型与算法综述
随着全球化和人工智能的发展,以及新冠肺炎的爆发,无人驾驶汽车在货物配送中发挥了重要作用。为了更好地分析无人车配送的研究方向,本文总结了无人车配送优化的模型和算法。研究结果表明,大多数研究都确立了优化总成本或旅行时间的目标。许多研究人员已经开始研究多目标优化问题,但存在一定的局限性,因此一些研究将这些问题转化为单目标优化来解决,例如将时间和能耗转化为成本,将等待时间转化为距离,将时间延迟转化为惩罚成本。随着无人车配送技术的发展,在未来的研究中,应该建立并求解一个成本最低、距离最短、安全性最好的多目标模型。大多数研究都提出了求解无人车分配问题的启发式算法,并得到了改进的优化解。为了保证求解方法的多样性,并兼顾求解时间和求解质量,与其他算法的混合方法将是未来的研究方向,例如启发式算法和精确算法的结合。随着研究的逐步深入,多种类型无人设备的集成分布将成为未来研究的重点。
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来源期刊
CiteScore
13.60
自引率
6.30%
发文量
402
审稿时长
15 weeks
期刊介绍: The Journal of Traffic and Transportation Engineering (English Edition) serves as a renowned academic platform facilitating the exchange and exploration of innovative ideas in the realm of transportation. Our journal aims to foster theoretical and experimental research in transportation and welcomes the submission of exceptional peer-reviewed papers on engineering, planning, management, and information technology. We are dedicated to expediting the peer review process and ensuring timely publication of top-notch research in this field.
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